code: def __init__(
      self,
      num_parallel_samples: int = 100,
      prediction_interval_length: float = 5.0,
      context_interval_length: float = 5.0,
  ) -> None:
      super().__init__()
      self.num_parallel_samples = num_parallel_samples
      self.prediction_interval_length = prediction_interval_length
      self.context_interval_length = context_interval_length
  
file_path: gluonts/test/mx/model/tpp/test_tpp_predictor.py
imports: from typing import Tuple
  import mxnet
  import numpy
  import pandas
  from pandas.tseries.frequencies import to_offset
  import pytest
  from mxnet import nd
  from gluonts.mx import PointProcessGluonPredictor, PointProcessSampleForecast
  from gluonts.mx import Tensor
  from gluonts.transform import ContinuousTimeInstanceSplitter, ContinuousTimePredictionSampler
  from .common import point_process_dataset, point_process_dataset_2
label_desc: Use image node_id 1 to create a new MockTPPPredictionNet object from inherited base classes: mx.gluon with example: obj = MockTPPPredictionNet(num_parallel_samples, prediction_interval_length, context_interval_length)